AI Platform Engineer

This is a fully remote position, open to applicants in Germany.

📋 Description

• Design and manage platforms for the deployment, monitoring, and maintenance of production AI models and services.

• Facilitate model-serving environments, inference pipelines, deployment processes, and automation of releases.

• Create automation for model packaging, promotion, validation, rollout, rollback, and lifecycle management.

• Establish monitoring, logging, alerting, and observability for AI services, focusing on performance, latency, availability, error rates, and costs.

• Collaborate with AI Engineers to transition models, workflows, and AI services from prototype to production.

• Work with cloud platform, infrastructure, and application teams to guarantee that AI services operate in secure, scalable, and reliable environments.

• Aid in defining operational standards for production AI systems, encompassing runbooks, incident response, testing, and release readiness.

• Provide support for both batch and real-time AI workloads where applicable.

• Diagnose issues related to model serving, API functionality, environment setup, infrastructure, and deployment pipelines.

• Develop reusable patterns for AI service deployment and integration across Deluxe applications.

• Contribute to the assessment and adoption of MLOps tools, model-serving frameworks, observability platforms, and AI infrastructure technologies.

⛳️ Requirements

• Proven experience in MLOps, AI platform engineering, DevOps, software engineering, or production ML operations.

• Background in deploying or managing AI/ML models, inference services, data services, or API-based production systems.

• Proficient scripting or programming skills in Python or similar languages.

• Familiarity with containers, CI/CD, cloud environments, monitoring, and operational automation.

• Knowledge of model deployment concepts, model lifecycle management, versioning, validation, and rollback processes.

• Experience in troubleshooting production systems across application, model, infrastructure, and deployment layers.

• Preferred: Familiarity with model-serving frameworks, MLOps platforms, Kubernetes, Docker, ECS, EKS, MLflow, KServe, BentoML, Ray, Airflow, or equivalent technologies.

• Preferred: Experience in supporting LLMs, agentic workflows, RAG systems, speech models, translation models, or other applied AI services.

• Preferred: Experience with GPU-backed inference, batch processing, distributed systems, or high-throughput workloads.

• Preferred: Knowledge of AWS services related to compute, storage, networking, security, monitoring, and deployment.

• Preferred: Background in media, localization, dubbing, content workflows, ASR, MT, TTS, or language technologies.

• Preferred: Experience in evaluating or integrating commercial and open-source AI platforms.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health, dental, and vision insurance.

• Opportunities for professional development and continuous learning.

• Flexible work hours and remote work options.

• A collaborative and inclusive work environment.